Method and equipment for assessing the life of members put under high in-service temperature environment for long period

ABSTRACT

For each component which is used at a high in-service temperature for a long period, its creep damage degree is approximated by a relational expression containing the Larson-Miller parameter. The creep damage degree is estimated by an approximation expression obtained by determining constants for each component. The creep damage degree is subjected to Weibull statistical analysis to estimate the creep damage degree probabilistically. Also, the thermal fatigue and damage degree obtained by an approximation expression is likewise subjected to Weibull statistical analysis to estimate the thermal fatigue and damage degree probabilistically. Therefore, the probabilistically estimated creep damage degree and the probabilistically estimated thermal fatigue and damage degree allows the life of each component subjected to a high in-service temperature to be assessed precisely and quickly.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based upon and claims the benefit of priority fromthe prior Japanese Patent Applications No. 2000-114126, filed Apr. 14,2000; and No. 2001-006859, filed Jan. 15, 2001, the entire contents ofboth of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

The present invention relates to a method and equipment for assessingthe duration of life of members put under a high in-service temperatureenvironment for a long period and more specifically to a method andequipment for assessing the duration of life of each member put under ahigh in-service temperature environment for a long period, for example,the high or intermediate pressure rotor, the high or intermediatepressure casing, and the main stop valve, that are incorporated into asteam turbine unit.

Conventionally, a member which is put under a high in-servicetemperature environment for a long period, for example, the rotor in asteam turbine unit, is subjected continuously to a load for a longperiod in a high in-service temperature environment and hence sufferscreep damage; as a consequence, its duration of life is reduced. Also,the rotor is repeatedly subjected to thermal stresses at the times ofstarting and stopping the turbine, resulting in the reduced duration oflife. To ensure the reliability of the steam turbine unit over a longperiod, therefore, it is important to assess the duration of life of itsstructural members with precision.

Heretofore, as a technique to assess the life of such members, one hasbeen developed and put to practical use which involves subjecting virginmaterials for new components and used materials of components which havebeen put at high in-service temperatures and are to be scrapped at thetime of replacement to a destructive test and assessing their residuallife on the basis of the material characteristic test results. That is,in the destructive test, the creep rupture strength and the low-cyclefatigue strength of those materials are obtained on a laboratory basis.The creep rupture strength and the low-cycle fatigue strength areobtained as a function of a certain parameter, for example, a functionof hardness. In inspecting a steam turbine unit regularly, the hardnessof the individual members is measured as their intrinsic parameter. Fromthe intrinsic parameters of the individual members, i.e., the creeprupture strength and low-cycle fatigue strength data as a function ofhardness, the operation history of the unit and its residual lifeallowing for future operation are assessed.

An example of a technique to assess the residual life is one disclosedin Jpn. Pat. Appln. KOKAI No. 1-27378. The technique of residual lifeassessment disclosed in this publication involves calculating thetemperature-stress characteristic of a structural member subjected to ahigh in-service temperature from its working condition value,calculating the material characteristic of the structural member fromits hardness, calculating the damage cumulative value of the structuralmember by adding corrections corresponding to the operation history tothese characteristics by condition setup equipment, and comparing thedamage cumulative value with an allowable value. It is said that such atechnique can predict accurately the time when a crack is initiated inthe structural member.

Conventionally, the life of individual members is obtained for eachunit. In this life assessment, the creep damage and the thermal fatiguedamage or low-cycle fatigue damage are obtained by linear cumulativedamage rules and a method to assess the residual life allowing forfuture operation is adopted. Thus, the conventional methods, whichassess the residual life for each unit or for each member in each unit,can produce variations in assessment and cannot make assessment quickly.From this point of view, the development of a technique to assess theresidual life of structural members precisely and quickly has beendemanded in recent years.

Conventionally, in assessing the life of a member in a turbine or thelike, its hardness is measured at regular inspection (in-serviceinspection) time and the life is assessed utilizing the measuredhardness. Unless the hardness is measured at regular inspection time,life assessment cannot be made with precision. It is difficult tomeasure the hardness at any desired time.

To ensure precise and quick life assessment, a method is required whichcollects changes with time in the hardness of each individual member andstochastically estimates the hardness of a member in a turbine or thelike to thereby assess its life.

BRIEF SUMMARY OF THE INVENTION

It is an object of the present invention to provide a method andequipment which permit the life of a structural member put under a highin-service temperature environment to be assessed precisely and quickly.

It is another object of the present invention to provide a method andequipment which, by collecting changes with time in the hardness of eachindividual member put under a high in-service temperature environment,permits its hardness to be estimated stochastically and its life to beassessed precisely and quickly.

According to an aspect of the present invention, there is provided amethod of assessing the life of a member subjected to a high in-servicetemperature for a long period comprising the steps of:

determining a Larson-Miller parameter for the member whose life is to beassessed from the in-service temperature and a service time periodduring which the member is used in-service temperature, and calculatingthe creep damage degree on the basis of cumulative damage rules from thehardness and stress of the member to establish data; and

approximating the relationship between the Larson-Miller parameter andthe creep damage degree by an expression including an exponentialfunction.

According to an aspect of the present invention there is also provided amethod of assessing the life of a member subjected to a high in-servicetemperature for a long period comprising the steps of:

determining a Larson-Miller parameter for the member whose life is to beassessed from the in-service temperature and service time period duringwhich the member is used in-service temperature and using dataestablished by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member toapproximate the relationship between the Larson-Miller parameter and thecreep damage degree by an expression including an exponential function;and

estimating the creep damage degree by adding probabilistic statisticalprocessing to the approximate expression.

Furthermore, according to an aspect of the present invention there isprovided a method of assessing the life of a member provided in anapparatus which is started and stopped over and over again and subjectedto a high in-service temperature for a long period while the apparatusis being operated comprising the steps of:

calculating an estimation parameter which is a function of a set of thestart count and thermal stress, and thermal fatigue and damage degreebased on cumulative damage rules for the member whose life is to beassessed and establishing data; and

approximating the relationship between the estimation parameter and thethermal fatigue and damage degree by an approximate expression.

According to an another aspect of the present invention, there is alsoprovided an apparatus for assessing the life of a member subjected to ahigh in-service temperature for a long period, comprising:

means for determining a Larson-Miller parameter for the member whoselife is to be assessed from the in-service temperature and a servicetime period during which the member is used in-service temperature, andcalculating the creep damage degree on the basis of cumulative damagerules from the hardness and stress of the member to establish data; and

means for approximating the relationship between the Larson-Millerparameter and the creep damage degree by an expression including anexponential function.

According to an yet another aspect of the present invention, there isalso provided an n apparatus for assessing the life of a membersubjected to a high in-service temperature for a long period comprising:

means for determining a Larson-Miller parameter for the member whoselife is to be assessed from the in-service temperature and service timeperiod during which the member is used in-service temperature and usingdata established by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member toapproximate the relationship between the Larson-Miller parameter and thecreep damage degree by an expression including an exponential function;and

means for estimating the creep damage degree by adding probabilisticstatistical processing to the approximate expression.

Furthermore, according to a yet another aspect of the present invention,there is provided an apparatus for assessing the life of a memberprovided in an apparatus which is started and stopped over and overagain and subjected to a high in-service temperature for a long periodwhile the apparatus is being operated comprising:

means for calculating an estimation parameter which is a function of aset of the start count and thermal stress, and thermal fatigue anddamage degree based on cumulative damage rules for the member whose lifeis to be assessed and establishing data; and

means for approximating the relationship between the estimationparameter and the thermal fatigue and damage degree by an approximateexpression.

Furthermore, according to a yet further aspect of the present invention,there is also provided an apparatus for assessing the life of a memberprovided in an apparatus which is started and stopped over and overagain and subjected to a high in-service temperature for a long periodwhile the apparatus is being operated comprising:

means for using an estimation parameter which is a function of the startcount and thermal stress, and data established by calculating thermalfatigue and damage degree based on cumulative damage rules, for themember whose life is to be assessed, and approximating the relationshipbetween the estimation parameter and the thermal fatigue and damagedegree by an approximate expression; and

means for estimating the thermal fatigue and damage degree by addingprobabilistic statistical processing to this approximate expression.

Furthermore, according to a yet another aspect of the present invention,there is provided a method of assessing the life of a member subjectedto a high in-service temperature for a long period comprising the stepsof:

determining a Larson-Miller parameter for the member whose life is to beassessed from the in-service temperature and time of the member andusing data established by calculating the creep damage degree on thebasis of cumulative damage rules from the hardness and stress of themember to approximate the relationship between the Larson-Millerparameter and the creep damage degree by an expression including anexponential function;

prompting a terminal connected through a network to input the in-servicetime period, of the member whose life is to be assessed;

assessing the life of the member from the in-service time period, of themember whose life is to be assessed by using the approximate expression;and

outputting the assessed life to the terminal.

According to a yet further aspect of the present invention, there isprovided an apparatus for assessing the life of a member subjected to ahigh in-service temperature for a long period comprising:

means for determining a Larson-Miller parameter for the member whoselife is to be assessed from the in-service temperature and time of themember and using data established by calculating the creep damage degreeon the basis of cumulative damage rules from the hardness and stress ofthe member to approximate the relationship between the Larson-Millerparameter and the creep damage degree by an expression including anexponential function;

means for prompting a terminal connected through a network to input thein-service time period, of the member whose life is to be assessed;

means for assessing the life of the member from the in-service timeperiod, of the member whose life is to be assessed by using theapproximate expression; and

means for outputting the assessed life to the terminal.

According to a yet further aspect of the invention, there is provided anapparatus for assessing the life of a member subjected to a highin-service temperature for a long period comprising:

means for determining a Larson-Miller parameter for the member whoselife is to be assessed from the in-service temperature and service timeperiod during which the member is used in-service temperature and usingdata established by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member toapproximate the relationship between the Larson-Miller parameter and thecreep damage degree by an expression including an exponential functionand further to prepare an expression estimating the creep damage degreeadded with probabilistic statistical processing;

means for prompting a terminal connected through a network to input thein-service time period, and the hardness of the member whose life is tobe assessed;

means for assessing the life of the member from the in-service timeperiod, of the input member; and

means for outputting the assessed life to the terminal.

In the above described method and apparatus, the Larson-Miller parameterP is calculated by an expression given as

P=(T+273)(log t+C)

where C is the material constant, T is the in-service temperature and tis the in-service time period, and the creep damage degree φc based uponthe cumulative damage rules is calculated by an expression given as

P′=A1(σ)H+B1(σ)

where σ is the stress, and H is the hardness,

P′=(T+273)(log tr+C)

where C is the material constant, T is the in-service temperature, andtr is creep rupture life,

φc=t/(tr+t) or φc=t/tr

where φc is the creep damage degree, and

where, when data of the hardness of the portion under a high in-servicetemperature and a high stress of the member whose life is to be assessedis used, φc=t/(tr+t) is employed, and when data of the hardness of theportion under a high in-service temperature and a low stress is used toassess the portion of the member under a high in-service temperature anda high stress, φc=t/tr is employed.

In the above described method and apparatus, the creep damage degree φcis obtained by

φc=1−exp(A·P ^(B))

wherein A and B are constants and P is the Larson-Miller parameter.

In the above described method and apparatus, the creep damage degreewhere the probabilistic statistical processing is added to theapproximate expression is also estimated by an expression given as

φc={1−exp(A·P ^(B))}·{β·^(m) {square root over (ln(1−Pf)⁻¹)}}

where m is the Weibull coefficient, β is the scale parameter, and Pf isthe cumulative probability.

the cumulative probability Pf corresponds to the cumulative probabilityPf defined by the following expression and the cumulative probability Pfdepending on the hardness is obtained by an expression given as

Pf=1−exp{−(μ/β)^(m)}

where m is the Weibull coefficient, β is the scale parameter, and μ isthe hardness of the member (experimental value)/the hardness of themember (estimated value), and

further the estimated value of the hardness of the member is obtained byan equation using the least squares method given as

at+b,

where t is the total operation time when the hardness of the member ismeasured, and a and b are constants.

In the above described method and apparatus, the hardness of the memberis estimated by a probabilistic expression given as

H=(at+b)(β·^(m){square root over (ln(1−Pf)⁻¹)})

wherein H is the hardness of the member, t is the total operation timewhen the hardness of the member is measured, a and b are constants, m isthe Weibull coefficient, β is the scale parameter, and Pf is thecumulative probability corresponding to the hardness of the member.

In the above described method and apparatus, the estimation parameter qis given by an expression of

 q=N(σc·nc/N+σw·nw/N+σh·nh/N)^(α)

where α is the constant, σc is the thermal stress of the member at coldstart time, σw is the thermal stress of the member at warm start time,σh is the thermal stress of the member at hot start time, N is the totalstart count, nc is the cold start count, nw is the warm start count, andnh is the hot start count, and the thermal fatigue and damage degree isapproximated by an expression given as

φf=C·q

where Cf is a constant.

In the above described method and apparatus, the thermal fatigue anddamage degree obtained by adding the probabilistic statisticalprocessing to the approximate expression is given by an expression of

φf=Cf·q(β·^(m){square root over (ln(1−Pf)⁻¹)})

where m is the Weibull coefficient, β is the scale parameter, and Pf isthe cumulative probability.

Additional objects and advantages of the invention will be set forth inthe description which follows, and in part will be obvious from thedescription, or may be learned by practice of the invention. The objectsand advantages of the invention may be realized and obtained by means ofthe instrumentalities and combinations particularly pointed outhereinafter.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

The accompanying drawings, which are incorporated in and constitute apart of the specification, illustrate presently preferred embodiments ofthe invention, and together with the general description given above andthe detailed description of the preferred embodiments given below, serveto explain the principles of the invention.

FIGS. 1A and 1B are block diagrams of equipment for assessing the lifeof a member put under a high in-service temperature environment for along period based on the creep rapture damage degree in accordance withan embodiment of the present invention;

FIG. 2 is a graph showing a relationship between a creep damage degree φand the Larson-Miller parameter P;

FIGS. 3A and 3B form a block diagram of equipment for assessing the lifeof a member put under a high in-service temperature environment for along period based on the thermal fatigue and damage degree in accordancewith another embodiment of the present invention;

FIG. 4 is graph showing a relation ship between a thermal fatigue anddamage degree φf and estimation parameter of the thermal fatigue anddamage degree q;

FIGS. 5A to 5C form a block diagram illustrating a more specificembodiment of equipment for assessing the life of a member put under ahigh in-service temperature environment for a long period in accordancewith the present invention;

FIG. 6 is a graph showing the results of assessment of the stochasticcreep damage degree of a turbine member obtained by steam turbinemember's life assessment equipment of the present invention;

FIG. 7 is a graph showing the results of assessment of the stochasticthermal fatigue and damage degree of a turbine member obtained by steamturbine member's life assessment equipment of the present invention;

FIG. 8 is a block diagram of a modification of the equipment forassessing the life of a member put under a high in-service temperatureenvironment for a long period in accordance with the present invention;

FIG. 9 is a detailed block diagram of the section for estimating thestochastic hardness of the turbine member shown in FIG. 8;

FIG. 10 is a characteristic diagram showing the relationship ofoperating time and hardness for use in explanation of calculations inthe section for estimating the stochastic hardness of the turbine membershown in FIG. 8;

FIG. 11 is a characteristic diagram showing variations in data in therelationship of operating time and hardness for use in explanation ofcalculations in the estimation of the stochastic hardness of the turbinemember shown in FIG. 8;

FIG. 12 is a block diagram of the section for assessing the thermalfatigue and damage of the turbine member shown in FIG. 8;

FIG. 13 is a block diagram of the means for assessing the creep damageof the turbine member shown in FIG. 8; and

FIG. 14 is a schematic illustration of a system adapted to transmit theresults of assessment by the life assessment method and equipment shownin FIG. 8 over the Internet.

DETAILED DESCRIPTION OF THE INVENTION

Hereinafter, the method and equipment for assessing the life of a memberthat is put under a high in-service temperature environment for a longperiod, in accordance with the present invention will be described withreference to the accompanying drawings.

The method of life assessment of the invention is generalized such thatthe creep damage degree and the thermal fatigue and damage degree of astructural member which is put under a high in-service temperatureenvironment for a long period are calculated on the basis of cumulativedamage rules, the calculated creep damage degree and thermal fatigue anddamage degree are stored as data in a storage device, and the residuallife of that member is predicted and analyzed probabilistically usingboth data on the basis of the Weibull statistical analysis.

In this life assessment, the material strength characteristic isestimated from hardness data and its life is predicted based on thosedata, history data, design data.

Hereinafter, an embodiment of equipment for assessing the life of amember which is put under a high in-service temperature environment fora long period will be described with reference to the drawings.

FIGS. 1A and 1B are functional block diagrams for use in explanation ofthe equipment for assessing the life of a structural member used at ahigh in-service temperature in accordance with the present invention. Asystem that estimates probabilistically the creep damage degree of asteam turbine member includes functions shown in FIG. 1A. That is, theestimation system is composed of an input section 1 for inputting dataconcerning a member in a steam turbine, a storage section 2 for storingthe data, a calculation section 3 for calculating the creep damagedegree on the basis of the data, a storage section 4 for storing thecalculated value from the calculation section, and a calculation section5 for estimating the creep damage degree using a certain approximationexpression.

The data concerning the member in the steam turbine entered into thedata input section 1 include assessed component data, design data,inspection data, and operation history data. The assessed component dataincludes the unit name of a component as the subject of residual lifeassessment, the material name of the component, and the region name ofthe component. The design data includes the temperature T and the stressσ to which the structural member is subjected during the steady-stateoperation of the steam turbine. The inspection data includes thehardness (Vickers hardness) H of the structural member measured at thetime of in-service inspection of the steam turbine. The operationhistory data is the total operation time of the steam turbine.

The storage section 2 is stored with the assessed component data, thedesign data, the inspection data, and the operation history data inputfrom the input section 1 of data relating to the steam turbine member.Those data are accessed and output when they are needed in thecalculation sections 3 and 5.

The creep damage degree calculation section 3 calculates the creepdamage degree φc on the basis of pre-stored expressions (1) through (4).

At the time of steady operation under conditions of a high in-servicetemperature and a constant stress, creep damage occurs in each memberand its creep rupture dame degree φc can be estimated from the hardnessH and the stress, i.e., steady-state stress a through the Larson-Millerparameter P′ given by

P′=A1(σ)H+B1(σ)  (1)

where σ is the stress, H is the Vickers hardness and so on, and A₁ andB₁ are constants.

On the other hand, the Larson-Miller parameter P′ is represented, as afunction of the in-service temperature T(K) and the creep rupture lifetr, by

P′=(T+273)(log tr+C)  (2)

where C is the material constant.

Thus, by measuring the hardness H of a member at the time of in-serviceinspection of the steam turbine or estimating the hardness of the memberat a certain point of time as will be described later, knowing thein-service temperature T (K) and the stress σ allows the life up to thetime the member undergoes creep rupture life time or period tr to beestimated by

tr=10^({P′/(T+273)−C})  (3)

where C is the material constant, T is the in-service temperature, andtr is creep rupture life,

φc=t/(tr+t) or φc=t/tr  (4)

where φc is the creep damage degree, and

where, when data of the hardness of the portion under a high in-servicetemperature and a high stress of the member whose life is to be assessedis used, φc=t/(tr+t) is employed, and when data of the hardness of theportion under a high in-service temperature and a low stress is used toassess the portion of the member under a high in-service temperature anda high stress, φc=t/tr is employed.

The stored data of the creep damage degree φc has a relationship withthe Larson-Miller parameter P as shown in FIG. 2, wherein the creepdamage degrees φc are plotted in a relation of the Larson-Millerparameter P.

The computational results from the calculation section 3 are retained inthe storage section 4 where they are stored for each member and eachregion. Specifying the name of a member or region allows its associatedcomputational results to be accessed. Thus, the calculation resultstorage section 4 is stored with combined data of the creep damagedegree φc and the Larson-Miller parameter P for each of many members andassessment regions.

Next, in the creep damage degree estimation approximation expressioncalculation section 5, an approximation expression for the creep damagedegree φc is calculated from expression (5) representing therelationship of the creep damage degree φc and the Larson-Millerparameter P for each assessment region of each component. Theapproximation expression (5) is decided by combined data of the creepdamage degree φc and the Larson-Miller parameter P stored in the storagesection 4 for each assessment region of each individual member. That is,constants A and B in approximation expression (5) are obtained for eachregion of each member. The creep damage degree φc is estimated byapproximation expression (5) representing the relationship of P and φc.

φc=1−exp(A·P ^(B))  (5)

where A and B are constants.

Experiments have confirmed that approximation expression (5) is veryclose to the relationship of the creep damage degree φc and theLarson-Miller parameter P_measured actually for members of a steamturbine.

Next, as shown in FIG. 1B, the estimated creep damage degree φc is inputfrom the creep damage degree estimation approximation expressioncalculation section 5 to a system that estimates the probabilistic life.This system is composed of a section 6 for Weibull statisticalprocessing and a calculation section 7 for a probabilistic estimationexpression of the creep damage degree φc.

In the Weibull statistical processing section 6, the estimated creepdamage degree φc is subjected to Weibull statistical analysis. In theprobabilistic estimation expression calculation section 7, theprobabilistic life is predicted from the analyses.

Variations in data in the relationship of the creep damage degree φc andthe Larson-Miller parameter P as a function of the operation time periodt(h) and the in-service temperature T(K) can be closely approximated bythe Weibull distribution, and the Weibull coefficient m and the scaleparameter β are calculated through the Weibull statistical analysis.

The creep damage degree probabilistic estimation expression calculationsection 7 calculates an expression to estimate probabilistically thecreep damage degree φc as

φc={1−exp(A·P ^(B))}·{β·^(m){square root over (ln(1−Pf)⁻¹)}}  (6)

FIGS. 3A and 3B form a block diagram of another embodiment of theequipment for assessing the life of structural members used at a highin-service temperature in accordance with the present invention. In thesystem shown in FIG. 3A, the probabilistic thermal fatigue and damagedegree of a steam turbine member is estimated. This system is composedof a data input section 1A for receiving data concerning a member in asteam turbine, a storage section 2A for storing the input data, acalculation section 8 for calculating the thermal fatigue and damagedegree, a storage section 9 for storing the calculated value from thecalculation section, and a calculation section 10 for determining anapproximation expression for estimating the thermal fatigue and damagedegree.

The data concerning a member in the steam turbine entered into the datainput section 1A include to-be-assessed component data, design data,inspection data, and operation history data. The to-be-assessedcomponent data includes the unit name, member name, and member regionname. The design data includes the in-service temperature T and stress σto which a structural member is subjected. Specifically, the stressincludes the cold stress σc at cold start time, for example, at starttime after the in-service inspection of the steam turbine, the warmthermal stress σw at warm start time, for example, at the time of startafter the weekend stoppage, and the hot thermal stress σh at hot starttime, for example, at everyday start time. The inspection data includesthe hardness (Vickers hardness) H of the structural member measured atin-service inspection time. The operation history data includes thestart count n representing the number of times a start has been made;specifically, the total start count N, the cold start count ncrepresenting the number of cold starts, the warm start count nwrepresenting the number of warm starts, and the hot start count nhrepresenting the number of hot starts.

The storage section 2A is stored with the to-be-assessed component data,the design data, the inspection data, and the operation history datainput from the data input section 1A.

The calculation section 8 includes a storage section for pre-storingexpressions (7) through (10). In the calculation section, various piecesof data stored in the storage section 2A are put into those expressions,then calculations are carried out in accordance with the expressions toobtain a thermal fatigue and damage degree φf (experimental value) andan estimation parameter q for the thermal fatigue and damage degree.

That is, being subjected to stresses repeatedly as the result of theturbine being started and stopped over and over again, a componentsuffers thermal fatigue and damage, which can be estimated in terms ofan elastic strain range Δεe. The elastic strain range Δεe is a functionof the number, M, of repetitions of start and stop until a componentcracks, or raptures and the hardness H of the component and representedby

Δεe=C ₁ M ^(α1) +C ₂ ·M ^(α2)  (7)

where C1=C₁=10^(β)1·^(H+β)2, α₁=β₃·H+β4, and C2, C₂, α₁, β₁, β₂, β₃, β₄are constants.

On the other hand, the elastic strain range Δεe of a region whose lifeis assessed is a function of strain concentration coefficient K, stressσ, and elastic coefficient E and represented by

Δεe=2Kε(σ/E)  (8)

Therefore, measuring the hardness H of an in-service member and knowingthe stress σ allow the number M of repetitions of start and stop, untila crack is produced in that member, to be estimated.

For the start count n, there are three patterns: cold start count nc,warm start count nw, and hot start count nh. Expression (9) thataccumulates the ratio, n/M, of the start count n to the repetition countM for each start pattern is defined to be the thermal fatigue and damagedegree φf.

φf=nc/Mc+nw/Mw+nh/Mh  (9)

On the other hand, even if the total start count N remains unchanged,the thermal fatigue and damage degree φf varies due to a stressresulting from a temperature difference between start and stop times anddifferent start patterns.

Thus, taking the start patterns, the start count and the stresses intoaccount, the thermal fatigue and damage degree estimation parameter q isobtained by

q=N(σc·nc/N+σw·nw/N+σh·nh/N)^(α)  (10)

where α is a constant, σc is the thermal stress at cold start time, σwis the thermal stress at warm start time, σh is the thermal stress athot start time, N is the total start count, nc is the cold start count,nw is the warm start count, and nh is the hot start count.

The thermal fatigue and damage degree φf and the thermal fatigue anddamage degree estimation parameter q thus calculated are output to thestorage section 9. In the storage section 9, therefore, the thermalfatigue and damage degree φf and the thermal fatigue and damage degreeestimation parameter q are stored in combination as data for eachto-be-assessed region or portion of each of many members.

FIG. 4 shows data plots indicating a relationship between the thermalfatigue and damage degree φf and the damage degree estimation parameterq, in which a linear function expressed by an approximation expression(11) explained as follows is also denoted. As apparent from FIG. 4, thedata plots can be substantially approximated to the linear function.

In the approximation expression calculation section 10, an approximationexpression for the thermal fatigue and damage degree φf is obtained,that indicates the relationship of the thermal fatigue and damage degreeφf and the thermal fatigue and damage degree estimation parameter q foreach to-be-assessed region of each component. The approximationexpression is calculated from combined data of the thermal fatigue anddamage degree φf and the thermal fatigue and damage degree estimationparameter q stored in the storage section 4 for each region of eachmember by expression (11), which represents a constant Cf, estimationparameter q and thermal fatigue and damage degree φf for each componentby a linear approximation expression.

φf=Cf·q  (11)

In expression (10) α is obtained for each region of each component, andan appropriate parameter value that most closely approaches expression(11) is calculated.

Next, as shown in FIG. 3B, the probabilistic residual life of thethermal fatigue and damage degree is predicted and analyzed. The systemof FIG. 3B is composed of a Weibull statistical processing calculationsection 11 for predicting and analyzing the probabilistic residual lifeof the thermal fatigue and damage degree on the basis of thecomputational results by the approximation expression calculationsection 10 of FIG. 3A and a thermal fatigue and damage degreeprobabilistic estimation calculation section 12.

The Weibull statistical processing calculation section 11 calculates theWeibull coefficient m and the scale parameter β by Weibull statisticalanalysis for grasping variations in field data quantitatively asdescribed in connection with FIG. 1B.

The thermal fatigue and damage degree probabilistic estimationcalculation section 12 can estimate the thermal fatigue and damagedegree φf probabilistically by substituting the Weibull coefficient mand the scale parameter β obtained by the Weibull statistical processingcalculation section 11 into the expression

φf=Cf·q(β·^(m){square root over (ln(1−Pf)⁻¹)})  (12)

where Pf is the cumulative probability (the probability of failure).

FIGS. 5A to 5C illustrate the function of a system comprising acalculation system that carries out calculations by an estimationexpression for estimating the life of a component probabilistically anda device for assessing its life in accordance with the calculations.

FIG. 5A and 5C show the calculation apparatus that carries outcalculations by an estimation expression for estimating the life of acomponent probabilistically. The calculation system comprises an optionsection 13 for determining items to be performed, a data input andstorage section 14 for inputting necessary data and storing it, a damagedegree calculation section 15 for calculating the damage degree, astorage section 16 for storing the calculation of the damage degree, aninput section 1B for inputting information about the object ofassessment, a calculation section 17 for calculating approximation andestimation expressions on the basis of data from the storage section 16,and a storage and output section 18 for storing the approximation andestimation expressions.

The option section 13 can selectively perform the following;

1) Calculates the creep damage degree and the thermal fatigue and damagedegree and stores the results in the storage section;

2) Obtains the approximation expression for estimating the creep damageand the expression for estimating probabilistically the creep damagedegree on calculations and obtains the approximation expression forestimating the thermal fatigue and damage degree and the expression forestimating probabilistically the thermal fatigue and damage degree oncalculations;

3) Assesses the life probabilistically.

A selection can be made among these options through select buttons (notshown) by way of example.

In the input and storage section 14, component data, operation historydata, inspection data, and design data are input and stored. Thecomponent data includes unit name, member name, region name, etc. Theoperation data includes start/stop count, operation time, etc. Theinspection data includes the hardness of a member, etc. The design dataincludes temperature, stress, etc.

The damage degree calculation section 15 calculates the creep damagedegree φc based on expression (4) and the thermal fatigue and damagedegree if based on expression (9) and stores the results in the storagesection 16.

In the input section 1B, data for a member or region for whichapproximation and estimation expressions are to be obtained is enteredand the object of estimation is identified. In the calculation section17, if M or more pieces of data have been obtained as the calculationsof the damage degree of the identified member and region, theapproximation expression for estimating the creep damage and theexpression for estimating probabilistically the creep damage degree arecalculated. Also, in the calculation section 17, the approximationexpression for estimating the thermal fatigue and damage degree and theexpression for estimating probabilistically the thermal fatigue anddamage degree are calculated likewise. In the storage and output section18, these expressions are stored and then output as required.

Next, a life assessment apparatus will be described with reference toFIG. 5C. The apparatus is composed of an estimation unit, component andregion data input section 23, a calculation section 24 for lifeassessment based on estimation expressions, and an output section 27 foroutputting the results of assessment.

In the data input section 23, data necessary for assessment, such asassessment unit, member, operation time, start/stop count, temperature,stress, and cumulative probability Pf, are input.

In the calculation section 24, the creep damage degree probabilisticestimation and the thermal fatigue and damage probabilistic estimationare performed, and in the output section 27 the results of estimationare output.

FIG. 6 shows the exemplary results of probabilistic estimation of thecreep damage degree φc of a turbine member by a steam turbine memberlife assessment device. FIG. 7 shows the exemplary results ofprobabilistic estimation of the thermal fatigue and damage degree φf.FIG. 6 plots the probabilistically estimated creep damage degree φc of amember of a steam turbine against the operation time for cumulativeprobability Pf=0.05, 0.87 and 0.95. In FIG. 7, the probabilisticallyestimated thermal fatigue and damage degree φf of the steam turbinemember is plotted against the start count of the steam turbine unit forcumulative probability Pf=0.05, 0.44 and 0.95.

The curves of FIGS. 6 and 7 confirm that, if the creep damage degree φcand the thermal fatigue and damage degree φf are delivered from thehardness which is measured at in-service inspection time and thecumulative probability Pf=0.87 and 0.44 are determined from theequations (6) and (12), the residual life can probabilistically bepredicted with precision based on the creep damage degree φc and thethermal fatigue and damage degree φf for each component of the steamturbine.

In this way, according to the equipment of this embodiment, the processof consumption of the life can be simulated for any cumulativeprobability Pf.

The above embodiment of the present invention has been described interms of the rotor of a steam turbine as a structural member used at ahigh in-service temperature. This is not restrictive. The principles ofthe present invention can be applied to any other structural member usedat high in-service temperatures.

Another embodiment of the present invention will be described withreference to FIGS. 8 to 13.

FIG. 8 shows equipment for assessing the life of a member. This lifeassessment equipment comprises an estimation section 51 for estimatingprobabilistically the hardness of a turbine member subjected to a highin-service temperature, an assessment or estimation section 52 forestimating or assessing the thermal fatigue and damage degree of theturbine member, and an assessment section 53 for assessing the creepdamage degree of the turbine member.

The estimation section 51 comprises a data input section 61 forinputting data concerning a member, a calculation section 62 forexecuting calculations in accordance with an expression that estimatesthe hardness of the member on the basis of the input data, and an outputsection 63 for outputting the results from the calculation section 62.In the estimation section 51, the hardness of the turbine member at anytime can be estimated on the basis of the Weibull statisticalanalysis-based probabilistic estimation expression as will be describedlater.

The estimation section 52 comprises a data input section 71 forinputting data concerning a member, a calculation section 72 forcalculating the thermal fatigue and damage degree on the basis of theinput data, and an output section 73 for outputting the results from thecalculation section 72. In the estimation section 52, the thermalfatigue and damage degree is estimated, or evaluated from the estimatedvalue for hardness from the section 51, and the thermal stress, thetemperature and the start count of the turbine member.

The estimation section 53 comprises a data input section 81 forinputting data concerning a member, a calculation section 82 forcalculating the creep damage degree, and an output section 33 foroutputting the results from the calculation section 82. In theestimation section 53, the creep damage degree is estimated, orevaluated from the estimated value for hardness from the section 51, andthe steady-state stress, the temperature and the operation time of theturbine member on the basis of cumulative damage rules.

In FIG. 9, the hardness estimation section 51 is illustrated in detail.As shown in FIG. 9, in the turbine member's life assessment equipment,time-varying hardness data is stored over a long period of time, say,fifteen years. The hardness of the turbine member is estimatedprobabilistically by subjecting the hardness data to Weibull statisticalanalysis.

A piece of each member is prepared at manufacture time. Its initialhardness at manufacture time and the subsequent hardness are examined.The hardness H is plotted against the operation time t as shown in FIG.10. It has been found that the plot of FIG. 10 can be approximated by alinear function as indicated by expression (33). In FIG. 10, thehardness H is represented in terms of Vickers hardness. Any other unitinstead of the Vickers hardness may represent the hardness. In this caseas well, the data plot of FIG. 10 can be made to approximate toexpression (33).

H=at+b  (33)

Also, it has been found that variations (μ=experimental value/estimatedvalue) in data in the relationship of the operation time and thehardness can be made to approximate closely to the Weibull distributionas shown in FIG. 11. The Weibull coefficient and the scale parameter cantherefore be determined from variations in data and the hardness H canbe estimated probabilistically by

H=(at+b)(β·^(m){square root over (ln(1−Pf)⁻¹)})  (34)

In the data input section 51 shown in FIG. 9, evaluation component data,hardness data and evaluation time data are input. Data concerning acomponent to be evaluated include the name of a unit into which thecomponent is incorporated (e.g., a steam turbine unit), the name of amember for identifying the material of the component, and the name ofthe component. For the hardness data, (i) when initial hardness isinput, the initial hardness H0 is input, (ii) when the hardness atn-service inspection time is input, the operation time t1 throughhardness measurement at in-service inspection time and the hardness H1are input, and (iii) when a cumulative probability Pf is directlyspecified, an appropriate cumulative probability Pf is input. For theevaluation time data, an evaluation time th through the time ofevaluation is input.

Further, in the calculation section 62 shown in FIG. 9, the hardness atevaluation time is estimated probabilistically by the estimationexpression as follows. That is, taking variations in the hardness of amember according to its material characteristics into account,cumulative probabilities Pf corresponding to the initial hardness andthe hardness at in-service inspection time are calculated in thecalculation section 121 as follow:

(i) When the initial hardness is input, the cumulative probability Pf0corresponding to the initial hardness is determined by

Pf0=1 −exp{−(μ0/β)^(m)}  (35)

where H is the member's hardness, t is the member's total operationtime, a and b are constants, m is the Weibull coefficient, β is thescale parameter, Pf is the cumulative probability corresponding to theinitial hardness of the member, and μ0 is initial hardness (experimentalvalue)/hardness (estimated value).

Here, initial hardness (experimental value)=H0

total operation time: t=t0=0

hardness of the member H=a t0+b=b

(ii) When the hardness at in-service inspection time is input, thecorresponding cumulative probability is determined by

Pf1=1 −exp{−(μ1/β)^(m)}  (36)

where μ1 is hardness at in-service inspection time (experimentalvalue)/hardness (estimated value).

Here, hardness at in-service inspection time (experimental value)=H1

total operation time: t=t1

hardness of the member H=a t0+b=b

(iii) When Pf is directly specified, the hardness can be estimatedutilizing the specified Pf and the evaluation time t.

Next, in the hardness calculation section 122, the hardness atevaluation time is calculated using the probabilities Pf0 and Pf1calculated by the calculation section 121 or the directly specified Pfand the total operation time t at evaluation time.

The hardness as the calculation result at the evaluation time and thecumulative probability Pf corresponding to the hardness at theevaluation time is output from the output section 63 shown in FIG. 9.

FIG. 12 shows the details of the turbine member thermal fatigue anddamage degree assessment section 52. In the data input section 71, inputdata include calculation data, component data, design data, andoperation data (operation history data). The calculation data is thehardness of a turbine member (corresponding to the output of the memberhardness estimation section 1). The component data includes the unitname, member name, and region name. The design data includes thetemperature T, the thermal stress σc at cold start time, the thermalstress σw at warm start time, the thermal stress σh at hot start time,and the generic thermal stress σ for these stresses. The operation dataincludes the total start count N, the cold start count nc, the warmstart count nw, and the hot start count nh.

In the calculation section 72 shown in FIG. 12, the thermal fatigue anddamage degree is calculated from the input data from the data inputsection 61 and the hardness H at evaluation time estimated by thehardness estimation section 51.

The thermal fatigue and damage degree of the member resulting from beingsubjected to repeated stresses due to the start and stop of the turbinecan estimate the strain range Δεe from a function of the number ofrepetitions N through the generation of a crack and the hardness H as alow-cycle fatigue characteristic by

Δεe=C1M ^(α1) +C2M ^(α2)  (37)

The strain range of Δεe of a life evaluation region is represented as afunction of the strain concentration coefficient Kε, the stress σ andthe elastic coefficient E as follows:

Δεe=2Kε(σ/E)  (38)

Therefore, knowing the stress σ allows the number of repetitions (thenumber of occurrences of rupture) M until cracking occurs in the turbinemember to be estimated using the hardness H at evaluation time obtainedby the hardness estimation section 51.

For the start count n, there are three patterns: cold start count nc,warm start count nw, and hot start count nh. The accumulation of theratio, n/M, of the start count n to the repetition count M through thetime of occurrence of cracking for each start pattern is defined to bethe thermal fatigue and damage degree φf as follows:

φf=nc/Mc+nw/Mw+nh/Mh  (39)

Here,

C₁=10^(β)1^(H+β)2,

α₁=β₃·H+β4, and

C₂, α₁, β₁, β₂, β₃, β₄ are constants, Δεe is the strain range of thelife assessment region, K is the strain concentration coefficient, σ isthe stress, M is the number of repetitions through the time ofoccurrence of cracking, E is the elastic coefficient, nc is the coldstart count, nw is the warm start count, nh is the hot start count, Mcis the number of repetitions through the time of occurrence of crackingat the cold start time, Mw is the number of repetitions through the timeof occurrence of cracking at the cold start time, Mh is the number ofrepetitions through the time of occurrence of cracking at the hot starttime, and φf is the thermal fatigue and damage degree.

FIG. 13 shows the details of the turbine member creep rupture and damagedegree assessment section 53. In the data input section 81, input datainclude calculation data, component data, design data, and operationdata (operation history data). The calculation data is the hardness of aturbine member (corresponding to the output of the member hardnessestimation section 51). The component data includes the unit name,member name, and region name. The design data includes the temperature Tof the turbine member in the steady state, the steady-state stress σ.The operation data includes the total operation time t.

In the estimation section 82 shown in FIG. 13, the creep damage degreeis calculated from the input data from the data input section 81 and thehardness H at evaluation time from the hardness estimation section 51.Specifically, the creep damage degree is estimated (calculated) based onexpressions (40) through (43).

The creep damage degree due to steady-state operation under conditionsof a high in-service temperature and a constant stress allows theLarsonMiller parameter P to be estimated from the hardness H and thesteady-state stress (load stress) by

P′=A1(σ)H+B1(σ)  (40)

On the other hand, the Larson-Miller parameter p is represented, as afunction of the in-service temperature T(° C.) and the creep rupturelife tr, by

tr=10^({p′/(T+273)−C})  (41)

where C is the material constant, T is the in-service temperature, andtr is creep rupture life,

φc=t/(tr+t) or φc=t/tr  (42)

where φc is the creep damage degree, and

where, when data of the hardness of the portion under a high in-servicetemperature and a high stress of the member whose life is to be assessedis used, φc=t/(tr+t) is employed, and when data of the hardness of theportion under a high in-service temperature and a low stress is used toassess the portion of the member under a high in-service temperature anda high stress, φc=t/tr is employed.

The estimation result of the creep damage degree is output from theoutput section 83 of FIG. 13.

In the calculation section 121 of FIG. 9, the cumulative probability Pfobtained from the hardness of a member at any point of time can beestimated on the basis of the probabilistic estimation expression basedon the Weibull statistical analysis; this cumulative probability Pf maybe input, as inspection data, to the input section 23 shown in FIG. 5Cto estimate the creep damage degree in the system of FIGS. 5A to 5C.

Furthermore, in the calculation section 121, the cumulative probabilityPf can be estimated. This cumulative probability Pf may be used toestimate the creep damage degree. That is, the cumulative probability Pfmay be so inputted to the input section 23 shown in FIG. 5C as toestimate the creep damage degree. The hardness H obtained from thecumulative probability Pf may be also so input to the input section 1Ashown in FIG. 1A to estimate the thermal fatigue and damage degree. Thatis, the cumulative probability may be utilized to estimate the thermalfatigue and damage degree.

As apparent from the description, the above described method and systemare realized by a computer system comprising CPU, ROM, RAM and I/F and acomputer program for the computer system is so designed as to performthe above described method.

FIG. 14 illustrates a method of assessing the life of a turbine memberover a network, for example, an internet 95. With the system of FIG. 14,a server 96 can provide a service over the internet 95 to a client whodesires to assess the life of a member consisting of low alloy steel.That is, in the system that assesses the life of a member, a terminal 94on the client side includes an input section 91 and an output section 92and the service providing server 96 includes an estimation section thatestimates the creep damage degree and the thermal fatigue and damagedegree which have already been described. The external input section 91is allowed to, as instructed by the server, enter the unit name, thecomponent name, the hardness, the operation time at the time of hardnessmeasurement or the cumulative probability Pf, and the operation time andthe start/stop count through the time of evaluation. The estimationsection receives those input data over the internet 95 and thenestimates the creep damage degree and the thermal fatigue and damagedegree. The output section 92 on the client side receives the results ofestimation over the internet 95 from the estimation and outputs them.

The external input section 91 is simply a device that inputs commandsand data to a computer such as a personal computer, for instance, akeyboard, a mouse, a tablet, a joystick, a scanner, an OCR, a characterrecognition system, a voice input system, a video system, a bar-codereader, or a microphone. The output section 92 may be any device capableof outputting computer-processed information, such as a printer, avisual display unit, a voice output system, etc.

The service providing server 96 consists of an information processingterminal, such as a computer, and has server functions for the internet95. The internet may be either wired or wireless provided that it canmake digital communications. The internet may contain public lines.

In the internet system as shown in FIG. 14, following methods can berealized. That is, the system can perform a method of assessing the lifeof a member subjected to a high in-service temperature for a long periodcomprising the steps of:

determining a Larson-Miller parameter for the member whose life is to beassessed from the in-service temperature and time of the member andusing data established by calculating the creep damage degree on thebasis of cumulative damage rules from the hardness and stress of themember to approximate the relationship between the Larson-Millerparameter and the creep damage degree by an expression including anexponential function;

prompting a terminal connected through a network to input the in-servicetime period, of the member whose life is to be assessed;

assessing the life of the member from the in-service time period, of themember whose life is to be assessed by using the approximate expression;and

outputting the assessed life to the terminal.

The system can also perform a method of assessing the life of a membersubjected to a high in-service temperature for a long period comprisingthe steps of:

determining a Larson-Miller parameter for the member whose life is to beassessed from the in-service temperature and service time period duringwhich the member is used in-service temperature and using dataestablished by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member toapproximate the relationship between the Larson-Miller parameter and thecreep damage degree by an expression including an exponential functionand further to prepare an expression estimating the creep damage degreeadded with probabilistic statistical processing;

prompting a terminal connected through a network to input the in-servicetime period, and the hardness of the member whose life is to beassessed;

assessing the life of the member from the in-service time period, of theinput member; and

outputting the assessed life to the terminal.

Furthermore, the system can perform a method of assessing the life of amember subjected to a high in-service temperature for a long periodcomprising the steps of:

inputting a service time period during which the member is usedin-service temperature, whose life is to be assessed from a terminalconnected to a network; and

according to the input, in a service supplying equipment connected tothe network, determining a Larson-Miller parameter for the member whoselife is to be assessed from the in-service temperature and service timeperiod during which the member is used in-service temperature, assessingthe life of the member by the approximate expression including anexponential function of the relationship between the Larson-Millerparameter and the creep damage degree using data established bycalculating the creep damage degree on the basis of cumulative damagerules from the hardness and stress of the member, and outputting theassessed life to the terminal.

Furthermore, the system can also perform a method of assessing the lifeof a member subjected to a high in-service temperature for a long periodcomprising the steps of:

inputting a service time period during which the member is usedin-service temperature and the hardness of the member whose life is tobe assessed from a terminal connected to a network; and

according to the input, in a service supplying equipment connected tothe network, determining a Larson-Miller parameter for the member whoselife is to be assessed from the in-service temperature and time of themember, using data established by calculating the creep damage degree onthe basis of cumulative damage rules from the hardness and stress of themember to approximate the relationship between the Larson-Millerparameter and the creep damage degree by an expression including anexponential function and to assess the life of the member by anexpression estimating the creep damage degree added with probabilisticstatistical processing, and outputting the assessed life to theterminal.

The system can also perform an another method of assessing the life of amember provided in an apparatus which is started and stopped over andover again and subjected to a high in-service temperature for a longperiod while the apparatus is being operated comprising the steps of:

from an estimation parameter which is a function of a set of the startcount and stress, and data established by calculating thermal fatigueand damage degree based on cumulative damage rules for the member whoselife is to be assessed, preparing an approximate expression of therelationship between the estimation parameter and the thermal fatigueand damage degree;

prompting a terminal connected through a network to input the startcount of the member whose life is to be assessed;

assessing the life of the member from the input start count by using theapproximate expression; and

outputting the assessed life to the terminal.

The system can also perform a yet another method of assessing the lifeof a member provided in an apparatus which is started and stopped overand over again and subjected to a high in-service temperature for a longperiod while the apparatus is being operated comprising the steps of:

using an estimation parameter which is a function of the start count andthermal stress, and data established by calculating thermal fatigue anddamage degree based on cumulative damage rules for the member whose lifeis to be assessed and approximating the relationship between theestimation parameter and the thermal fatigue and damage degree andpreparing an expression estimating the thermal fatigue and damage degreeadded with probabilistic statistical processing;

prompting a terminal connected through a network to input the startcount and the hardness of the member whose life is to be assessed;

assessing the life of the member from the input start count and hardnessby using the approximate expression; and

outputting the assessed life to the terminal.

Furthermore, the system can also perform an another method of assessingthe life of a member provided in an apparatus which is started andstopped over and over again and subjected to a high in-servicetemperature for a long period while the apparatus is being operatedcomprising the steps of:

inputting the start count of the member whose life is to be assessedfrom a terminal connected to a network; and

according to the input, in a service supplying equipment connected tothe network, assessing the life of the member by an approximateexpression of the relationship between the estimation parameter and thethermal fatigue and damage degree, which is approximated from anestimation parameter which is a function of the start count and thermalstress, and data established by calculating thermal fatigue and damagedegree based on cumulative damage rules for the member whose life is tobe assessed, and outputting the assessed life to the terminal.

The system can also perform a further method of assessing the life of amember provided in an apparatus which is started and stopped over andover again and subjected to a high in-service temperature for a longperiod while the apparatus is being operated comprising the steps of:

inputting the start count and hardness of the member whose life is to beassessed from a terminal connected to a network; and

according to the input, in a service supplying equipment connected tothe network, using an estimation parameter which is a function of thestart count and thermal stress, and data established by calculatingthermal fatigue and damage degree based on cumulative damage rules, forthe member whose life is to be assessed, approximating the relationshipbetween the estimation parameter and the thermal fatigue and damagedegree, assessing the life of the member by an expression estimating thethermal fatigue and damage degree added with probabilistic statisticalprocessing, and outputting the assessed life to the terminal.

As described thus far, the present invention provides the followingadvantages:

(1) Conventionally, in assessing the life of a turbine member, itshardness is measured at in-service inspection time and used to assessthe member's life. However, precise life assessment cannot be madewithout hardness measurement at in-service inspection time, resulting infailure to make quick life assessment. By contrast, the inventive lifeassessment method and equipment collect variations in hardness of themember with time and probabilistically estimates the hardness of theturbine member. If the initial hardness (hardness at manufacture time)or the hardness at in-service inspection time is available, then thehardness at the time of evaluation can be estimated based on thathardness and a cumulative probability Pf corresponding to the hardnesscan be determined.

(2) In the absence of hardness data, on the other hand, the hardness atevaluation time can be estimated by estimating the cumulativeprobability Pf. Even in the case where hardness data is known, thehardness corresponding to the cumulative probability Pf can be estimatedby specifying Pf.

(3) Moreover, the thermal fatigue material characteristic and the creepmaterial characteristic is determined as a function of hardness. The useof estimated hardness at evaluation time allows life assessment to bemade precisely and quickly.

(4) According to the present invention, the life assessment can bespeeded up and the life assessment cost can be reduced in any distantlocation by receiving input information over the internet 95 from aclient, assessing the life of a component through the use of theinventive assessment server, and sending the results of assessment tothe client.

According to the present invention, as described above, a lifeassessment method and equipment can be provided which permit the life ofa turbine member subjected to a high in-service temperature to beassessed by collecting the time-varying hardness of the member andestimating probabilistically the hardness of the turbine member.

Additional advantages and modifications will readily occur to thoseskilled in the art. Therefore, the invention in its broader aspects isnot limited to the specific details and representative embodiments shownand described herein. Accordingly, various modifications may be madewithout departing from the spirit or scope of the general inventiveconcept as defined by the appended claims and their equivalents.

What is claimed is:
 1. A method of assessing the life of a membersubjected to a high in-service temperature for a long period comprisingthe steps of: determining a Larson-Miller parameter for the member whoselife is to be assessed from the in-service temperature and a servicetime period during which the member is used in-service temperature, andcalculating the creep damage degree on the basis of cumulative damagerules from the hardness and stress of the member to establish data; andapproximating the relationship between the Larson-Miller parameter andthe creep damage degree by an expression including an exponentialfunction.
 2. The method according to claim 1, further comprising thestep of assessing the life of the member from the in-service temperatureand in-service time period, period of the member whose life is to beassessed using the approximate expression.
 3. The method according toclaim 1, wherein the Larson-Miller parameter P is calculated by anexpression given as P=(T+273)(log t+C) where C is the material constant,T is the in-service temperature and t is the in-service time period,period, and the creep damage degree φc based upon the cumulative damagerules is calculated by an expression given as P′=A(σ)H+B(σ) where σ isthe stress, and H is the hardness, P′=(T+273)(log tr+C) where C is thematerial constant, T is the in-service temperature, and tr is creeprupture life, φc=t/(tr+t) or φc=t/tr where φc is the creep damagedegree, and where, when data of the hardness of the portion under a highin-service temperature and a high stress of the member whose life is tobe assessed is used, φc=t/(tr+t) is employed, and when data of thehardness of the portion under a high in-service temperature and a lowstress is used to assess the portion of the member under a highin-service temperature and a high stress, φc=t/tr is employed.
 4. Themethod according to claim 3, wherein the relationship between theLarson-Miller parameter and the creep damage degree uses an approximateexpression including an exponential function given as φc=1−exp(A·P ^(B))where A and B are constants.
 5. A method of assessing the life of amember subjected to a high in-service temperature for a long periodcomprising the steps of: determining a Larson-Miller parameter for themember whose life is to be assessed from the in-service temperature andservice time period during which the member is used in-servicetemperature and using data established by calculating the creep damagedegree on the basis of cumulative damage rules from the hardness andstress of the member to approximate the relationship between theLarson-Miller parameter and the creep damage degree by an expressionincluding an exponential function; and estimating the creep damagedegree by adding probabilistic statistical processing to the approximateexpression.
 6. The method according to claim 5, wherein theLarson-Miller parameter P is calculated by an expression given asP=(T+273)(log t+C) where C is the material constant, T is a service timeperiod during which the member is used in-service temperature and t isthe in-service time period, and the creep damage degree φc based uponthe cumulative damage rules is calculated by an expression given asP′=A1(σ)H+B1(σ) where σ is the stress, and H is the hardness,P′=(T+273)(log tr+C) where C is the material constant, T is thein-service temperature, and tr is the creep rupture life, φc=t/(tr+t) orφc=t/tr where φc is the creep damage degree, and where, when data of thehardness of the portion under a high in-service temperature and a highstress of the member whose life is to be assessed is used, φc=t/(tr+t)is employed, and when data of the hardness of the portion under a highin-service temperature and a low stress is used to assess the portion ofthe member under a high in-service temperature and a high stress,φc=t/tr is employed.
 7. The method according to claim 6, wherein therelationship between the Larson-Miller parameter and the creep damagedegree uses an approximate expression including an exponential functiongiven as φc=1−exp(A·P ^(B)) where A and B are constants.
 8. The methodaccording to claim 7, wherein the creep damage degree where theprobabilistic statistical processing is added to the approximateexpression is estimated by an expression given as φc={1−exp(A·P^(B))}·{β·^(m){square root over (ln(1−Pf)⁻¹)}} where m is the Weibullcoefficient, β is the scale parameter, and Pf is the cumulativeprobability.
 9. The method according to claim 5, further comprising thestep of assessing the life of the member by inputting a cumulativeprobability into the expression added with the probabilistic statisticalprocessing.
 10. The method according to claim 9, wherein the cumulativeprobability is estimated from the hardness of the member.
 11. The methodaccording to claim 10, wherein the cumulative probability Pf correspondsto the cumulative probability Pf defined by the following expression andthe cumulative probability Pf depending on the hardness is obtained byan expression given as Pf=1−exp{−(μ/β)^(m)} where m is the Weibullcoefficient, β is the scale parameter, and μ is the hardness of themember (experimental value)/the hardness of the member (estimatedvalue), and further the estimated value of the hardness of the member isobtained by an equation using the least squares method given as at+b,where t is the total operation time when the hardness of the member ismeasured, and a and b are constants.
 12. The method according to claim9, wherein the step of assessing the life provides the graph regardingthe operation time of the member and the creep damage degree and theremaining life of the member.
 13. A computer program utilized in acomputer system, comprising steps of performing the method defined inclaim
 5. 14. A method of assessing the life of a member subjected to ahigh in-service temperature for a long period, wherein the hardness ofthe member is estimated by an expression given as H=(at+b)(β^(m){squareroot over (ln(1−Pf)⁻¹)}) wherein H is the hardness of the member, t isthe total operation time when the hardness of the member is measured, aand b are constants, m is the Weibull coefficient, β is the scaleparameter, and Pf is the cumulative probability corresponding to thehardness of the member.
 15. An apparatus for assessing the life of amember subjected to a high in-service temperature for a long period,comprising: means for determining a Larson-Miller parameter for themember whose life is to be assessed from the in-service temperature anda service time period during which the member is used in-servicetemperature, and calculating the creep damage degree on the basis ofcumulative rules from the hardness and stress of the member to establishdata; and means for approximating the relationship between theLarson-Miller parameter and the creep damage degree by an expressionincluding an exponential function.
 16. The apparatus according to claim15, further comprising means for assessing the life of the member fromthe in-service temperature and in-service time period, period of themember whose life is to be assessed using the approximate expression.17. The apparatus according to claim 15, wherein the Larson-Millerparameter P is calculated by an expression given as P=(T+273)(log t+C)where C is the material constant, T is the in-service temperature and tis the in-service time period, period, and the creep damage degree φcbased upon the cumulative damage rules is calculated by an expressiongiven as P′=A(σ)H+B(σ) where σ is the stress, and H is the hardness,P′(T+273)(log tr+C) where C is the material constant, T is thein-service temperature, and tr is creep rupture life, φc=t/(tr+t) orφc=t/tr where φc is the creep damage degree, and where, when data of thehardness of the portion under a high in-service temperature and a highstress of the member whose life is to be assessed is used, φc=t/(tr+t)is employed, and when data of the hardness of the portion under a highin-service temperature and a low stress is used to assess the portion ofthe member under a high in-service temperature and a high stress,φc=t/tr is employed.
 18. The apparatus according to claim 19, whereinthe relationship between the Larson-Miller parameter and the creepdamage degree uses an approximate expression including an exponentialfunction given as  φc=1−exp(A·P ^(B)) where A and B are constants. 19.An apparatus for assessing the life of a member subjected to a highin-service temperature for a long period comprising: means fordetermining a Larson-Miller parameter for the member whose life is to beassessed from the in-service temperature and service time period duringwhich the member is used in-service temperature and using dataestablished by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member toapproximate the relationship between the Larson-Miller parameter and thecreep damage degree by an expression including an exponential function;and means for estimating the creep damage degree by adding probabilisticstatistical processing to the approximate expression.
 20. The apparatusaccording to claim 19, wherein the Larson-Miller parameter P iscalculated by an expression given as P=(T+273)(log t+C) where C is thematerial constant, T is a service time period during which the member isused in-service temperature and t is the in-service time period, and thecreep damage degree φc based upon the cumulative damage rules iscalculated by an expression given as  P′=A1(σ)H+B1(σ) Where σ is thestress, and H is the hardness, P′=(T+273)(log tr+C) where T is thein-service temperature, and tr is the creep rupture life, φc=t/(tr+t) orφc=t/tr where φc is the creep damage degree, and where, when data of thehardness of the portion under a high in-service temperature and a highstress of the member whose life is to be assessed is used, φc=t/(tr+t)is employed, and when data of the hardness of the portion under a highin-service temperature and a low stress is used to assess the portion ofthe member under a high in-service temperature and a high stress,φc=t/tr is employed.
 21. The apparatus according to claim 20, whereinthe relationship between the Larson-Miller parameter and the creepdamage degree uses an approximate expression including an exponentialfunction given as φc=1−exp(A·P ^(B)) where A and B are constants. 22.The apparatus according to claim 21, wherein the creep damage degreewhere the probabilistic statistical processing is added to theapproximate expression is estimated by an expression given asφc={1−exp(A·P ^(B))}·{β·^(m){square root over (ln(1−Pf)⁻¹)}} where m isthe Weibull coefficient, β is the scale parameter, and Pf is thecumulative probability.
 23. The apparatus according to claim 19, furthercomprising the step of assessing the life of the member by inputting acumulative probability into the expression added with the probabilisticstatistical processing.
 24. The apparatus according to claim 23, whereinthe cumulative probability is estimated from the hardness of the member.25. The apparatus according to claim 23, wherein the cumulativeprobability Pf corresponds to the cumulative probability Pf defined bythe following expression and the cumulative probability Pf depending onthe hardness is obtained by an expression given as Pf=1−exp{−(μ/β)^(m)}where m is the Weibull coefficient, β is the scale parameter, and μ isthe hardness of the member (experimental value)/the hardness of themember (estimated value), and further the estimated value of thehardness of the member is obtained by an equation using the least squaremethod given as at+b, where t is the total operation time when thehardness of the member is measured, and a and b are constants.
 26. Theapparatus according to claim 19, wherein said assessing means providesthe graph regarding the operation time of the member and the creepdamage degree and the remaining life of the member.
 27. An apparatus forassessing the life of a member subjected to a high in-servicetemperature for a long period, wherein the hardness of the member isestimated by an expression given as H=(at+b)(β·^(m){square root over(ln(1−Pf)⁻¹)}) wherein H is the hardness of the member, t is the totaloperation time when the hardness of the member is measured, a and b areconstants, m is the Weibull coefficient, β is the scale parameter, andPf is the cumulative probability corresponding to the hardness of themember.
 28. A method of assessing the life of a member subjected to ahigh in-service temperature for a long period comprising the steps of:determining a Larson-Miller parameter for the member whose life is to beassessed from the in-service temperature and time of the member andusing data established by calculating the creep damage degree on thebasis of cumulative damage rules from the hardness and stress of themember to approximate the relationship between the Larson-Millerparameter and the creep damage degree by an expression including anexponential function; prompting a terminal connected through a networkto input the in-service time period, of the member whose life is to beassessed; assessing the life of the member from the in-service timeperiod, of the member whose life is to be assessed by using theapproximate expression; and outputting the assessed life to theterminal.
 29. A method of assessing the life of a member subjected to ahigh in-service temperature for a long period comprising the steps of:determining a Larson-Miller parameter for the member whose life is to beassessed from the in-service temperature and service time period duringwhich the member is used in-service temperature and using dataestablished by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member toapproximate the relationship between the Larson-Miller parameter and thecreep damage degree by an expression including an exponential functionand further to prepare an expression estimating the creep damage degreeadded with probabilistic statistical processing; prompting a terminalconnected through a network to input the in-service time period, and thehardness of the member whose life is to be assessed; assessing the lifeof the member from the in-service time period and the hardness, of theinput member; and outputting the assessed life to the terminal.
 30. Amethod of assessing the life of a member subjected to a high in-servicetemperature for a long period comprising the steps of: inputting aservice time period during which the member is used in-servicetemperature, whose life is to be assessed from a terminal connected to anetwork; and according to the input, in a service supplying equipmentconnected to the network, determining a Larson-Miller parameter for themember whose life is to be assessed from the in-service temperature andservice time period during which the member is used in-servicetemperature, assessing the life of the member by the approximateexpression including an exponential function of the relationship betweenthe Larson-Miller parameter and the creep damage degree using dataestablished by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member, andoutputting the assessed life to the terminal.
 31. A method of assessingthe life of a member subjected to a high in-service temperature for along period comprising the steps of: inputting a service time periodduring which the member is used in-service temperature and the hardnessof the member whose life is to be assessed from a terminal connected toa network; and according to the input, in a service supplying equipmentconnected to the network, determining a Larson-Miller parameter for themember whose life is to be assessed from the in-service temperature andtime of the member, using data established by calculating the creepdamage degree on the basis of cumulative damage rules from the hardnessand stress of the member to approximate the relationship between theLarson-Miller parameter and the creep damage degree by an expressionincluding an exponential function and to assess the life of the memberby an expression estimating the creep damage degree added withprobabilistic statistical processing, and outputting the assessed lifeto the terminal.
 32. An apparatus for assessing the life of a membersubjected to a high in-service temperature for a long period comprising:means for determining a Larson-Miller parameter for the member whoselife is to be assessed from the in-service temperature and time of themember and using data established by calculating the creep damage degreeon the basis of cumulative damage rules from the hardness and stress ofthe member to approximate the relationship between the Larson-Millerparameter and the creep damage degree by an expression including anexponential function; means for prompting a terminal connected through anetwork to input the in-service time period, of the member whose life isto be assessed; means for assessing the life of the member from thein-service time period, of the member whose life is to be assessed byusing the approximate expression; and means for outputting the assessedlife to the terminal.
 33. An apparatus for assessing the life of amember subjected to a high in-service temperature for a long periodcomprising: means for determining a Larson-Miller parameter for themember whose life is to be assessed from the in-service temperature andservice time period during which the member is used in-servicetemperature and using data established by calculating the creep damagedegree on the basis of cumulative damage rules from the hardness andstress of the member to approximate the relationship between theLarson-Miller parameter and the creep damage degree by an expressionincluding an exponential function and further to prepare an expressionestimating the creep damage degree added with probabilistic statisticalprocessing; means for prompting a terminal connected through a networkto input the in-service time period, and the hardness of the memberwhose life is to be assessed; means for assessing the life of the memberfrom the in-service time period, of the input member; and means foroutputting the assessed life to the terminal.
 34. An apparatus forassessing the life of a member subjected to a high in-servicetemperature for a long period, comprising: means for inputting a servicetime period during which the member is used in-service temperature,whose life is to be assessed from a terminal connected to a network; andmeans for according to the input, in a service supplying equipmentconnected to the network, determining a Larson-Miller parameter for themember whose life is to be assessed from the in-service temperature andservice time period during which the member is used in-servicetemperature, assessing the life of the member by the approximateexpression including an exponential function of the relationship betweenthe Larson-Miller parameter and the creep damage degree using dataestablished by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member, andoutputting the assessed life to the terminal.
 35. An apparatus forassessing the life of a member subjected to a high in-servicetemperature for a long period, comprising: means for inputting a servicetime period during which the member is used in-service temperature andthe hardness of the member whose life is to be assessed from a terminalconnected to a network; and means for according to the input, in aservice supplying equipment connected to the network, determining aLarson-Miller parameter for the member whose life is to be assessed fromthe in-service temperature and time of the member, using dataestablished by calculating the creep damage degree on the basis ofcumulative damage rules from the hardness and stress of the member toapproximate the relationship between the Larson-Miller parameter and thecreep damage degree by an expression including an exponential functionand to assess the life of the member by an expression estimating thecreep damage degree added with probabilistic statistical processing, andoutputting the assessed life to the terminal.